https://doi.org/10.4081/jae.2024.1611
Design and experiments of an integrated device for shrimp orientation and decapitation
Published: 16 October 2024
Abstract Views: 258
PDF: 133
HTML: 4
HTML: 4
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
To realize the automatic orientation and decapitation of shrimp, an integrated device for shrimp orientation and decapitation was designed based on the shape and size characteristics of shrimp, which was mainly composed of oriented rollers, shrimp pushing boards, adaptive clamping claw and knife for the decapitation of shrimp. Three kinds of shrimp of small, medium, and large size were selected. Taking the speed of the shrimp pushing boards, the horizontal speed of the adaptive clamping claw, the rotational speed of oriented rollers and the radius of the oriented rollers as the test factors, and the success rate of the shrimp decapitation as the index, the single factor test and the orthogonal test were carried out to study the effect of each factor on the shrimp decapitation, and then the main parameters of the device were optimized. The results showed that the optimal parameter combinations of the three sizes of shrimp were the speed of shrimp pushing plates of 60mm/s, the horizontal speed of adaptive clamping claw of 70mm/s, the rotational speed of oriented rollers of 60r/min, and the radius of oriented rollers of 20mm. Under the optimal combination of parameters, the device has the highest decapitation success rate and the success rate of shrimp decapitation was 91.5% for small shrimp, 94.6% for medium shrimp, and 92.8% for large shrimp, the decapitation speed was 36pcs/min for small shrimp, 38 pcs/min for medium shrimp, and 37 pcs/min for large shrimp. Therefore, the feasibility of the device design is verified.
Azarmdel, H., Mohtasebi, S.S., Jafari, A., Muñoz, A.R. 2019. Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision. Comput. Electron. Agr. 162:613-629.
DOI: https://doi.org/10.1016/j.compag.2019.05.005
Bibwe, B.R., Hiregoudar, S., Nidoni, U.R., Anantachar, M., Shrestha, B. 2013. Development of meat-bone separator for small scale fish processing. J. Food Sci. Technol. 50:763-769.
DOI: https://doi.org/10.1007/s13197-011-0381-5
Booman, A., Márquez, A., Parin, M.A., Zugarramurdi, A. 2010. Design and testing of a fish bone separator machine. J. Food Eng. 1003:474-479.
DOI: https://doi.org/10.1016/j.jfoodeng.2010.04.034
Chen, Q., Shen, J., Fu, R., Tan, J., Zhang, J. 2012. Research on the mechanical deheading method of typical small marine fish. Fish. Modern. 395:38-42.
Chen, Y., Jiao, M., Peng, X., Xu, C., Cai, L., Hu, Z., Ma, M. 2024. Study on positioning and detection of crayfish body parts based on machine vision. J. Food Meas. Charact. 18:4375-4387.
DOI: https://doi.org/10.1007/s11694-024-02500-2
Chen, Y., Mitra, A., Rahimnejad, S., Chi, S., Kumar, V., Tan, B., et al. 2024. Retrospect of fish meal substitution in Pacific white shrimp (Litopenaeus vannamei) feed: Alternatives, limitations and future prospects. Rev. Aquacult. 161:382-409.
DOI: https://doi.org/10.1111/raq.12843
Cheng, X., Li, M., Leng, X., Wen, H., Wu, F., Yu, L., et al. 2021. Creatine improves the flesh quality of Pacific white shrimp (Litopenaeus vannamei) reared in freshwater. Food Chem. 354:129498.
DOI: https://doi.org/10.1016/j.foodchem.2021.129498
Dang, T.T., Gringer, N., Jessen, F., Olsen, K., Bøknæs, N., Nielsen, P.L., Orlien, V. 2018. Emerging and potential technologies for facilitating shrimp peeling: A review. Innov. Food Sci. Emerg. 45:228-240.
DOI: https://doi.org/10.1016/j.ifset.2017.10.017
Dowgiallo, A. 2018. The Effect of cutting and fish-orientation systems on the deheading yield of carp. Int. J. Food Sci. Technol. 43:1688-1692.
DOI: https://doi.org/10.1111/j.1365-2621.2008.01750.x
Liu, J., Zhang, F., Wan, P., Tan, H. 2017. Freshwater fish pneumatic machinery to head-cutting method research. Food Machin. 331:87-92.
DOI: https://doi.org/10.1201/9781315375120-15
Liu, W., Lyu, J., Wu, D., Cao, Y., Ma, Q., Lu, Y., Zhang, X. 2022. Cutting techniques in the fish industry: a critical review. Foods 1120:3206.
DOI: https://doi.org/10.3390/foods11203206
Liu, Z., Liu, Q., Zhang, D., Wei, S., Sun, Q., Xia, Q., et al. 2021. Comparison of the proximate composition and nutritional profile of byproducts and edible parts of five species of shrimp. Foods 1011:2603.
DOI: https://doi.org/10.3390/foods10112603
Mesa, M.D., Gil, F., Olmedo, P., Gil, A. 2021. Nutritional importance of selected fresh fishes, shrimps and mollusks to meet compliance with nutritional guidelines of n-3 LC-PUFA intake in Spain. Nutrients 132:465.
DOI: https://doi.org/10.3390/nu13020465
N’Souvi, K., Sun, C., Che, B., Vodounon, A. 2024. Shrimp industry in China: overview of the trends in the production, imports and exports during the last two decades, challenges, and outlook. Front. Sustain. Food Syst. 7:1287034.
DOI: https://doi.org/10.3389/fsufs.2023.1287034
Nirmal, N.P., Santivarangkna, C., Rajput, M.S., Benjakul, S. 2020. Trends in shrimp processing waste utilization: An industrial prospective. Trends Food Sci. Technol. 103:20-35.
DOI: https://doi.org/10.1016/j.tifs.2020.07.001
Okpala, C.O.R., Bono, G. 2016. Investigating the biometric and physicochemical characteristics of freshly harvested Pacific white shrimp (Litopenaeus vannamei): a comparative approach. J. Sci. Food Agr. 964:1231-1240.
DOI: https://doi.org/10.1002/jsfa.7211
Omar, F.K., De Silva, C.W. 2000. Optimal portion control of natural objects with application in automated cannery processing of fish. J. Food Eng. 461:31-41.
DOI: https://doi.org/10.1016/S0260-8774(00)00068-6
Wang, Q., Tian, Y., Wang, J., Li, J.Y., He, W., Craig, N.J. 2023. Assessing pathways of heavy metal accumulation in aquaculture shrimp and their introductions into the pond environment based on a dynamic model and mass balance principle. Sci. Total Environ. 881:163164.
DOI: https://doi.org/10.1016/j.scitotenv.2023.163164
Wang, Y., Zhang, M., Mujumdar, A. S. 2011. Trends in processing technologies for dried aquatic products. Drying Technol. 294:382-394.
DOI: https://doi.org/10.1080/07373937.2011.551624
Zhang, D., Lillywhite, K.D., Lee, D.J., Tippetts, B.J. 2014. Automatic shrimp shape grading using evolution constructed features. Comput. Electron. Agr. 100:116-122.
DOI: https://doi.org/10.1016/j.compag.2013.11.009
Zhang, X., Wang, L., Yi, J., Wang, Z., Wang, J. 2017. Design and experiment of shrimp backside cutting machine formed by belt clamping and conveying. Trans. Chin. Soc. Agr. Eng. 3320:284-291.
Zhao, Z. 2005. Mechanized processing of dace. Fish. Modern. 337:36–37.
How to Cite
Ruan, P. (2024) “Design and experiments of an integrated device for shrimp orientation and decapitation”, Journal of Agricultural Engineering, 55(4). doi: 10.4081/jae.2024.1611.
Copyright (c) 2024 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Giacomo Scarascia-Mugnozza, Silvana Fuina, Sergio Castellano, Structural design and experimental tests on a model of tensegrity greenhouse prototype , Journal of Agricultural Engineering: Vol. 52 No. 3 (2021)
- Alessia Tonon, Lorenzo Picco, Diego Ravazzolo, Mario Aristide Lenzi, Using a terrestrial laser scanner to detect wood characteristics in gravel-bed rivers , Journal of Agricultural Engineering: Vol. 45 No. 4 (2014)
- Roberto Beghi, Simone V. Marai, Valentina Giovenzana, Enrico Ferrari, Riccardo Guidetti, Testing and design of a passive container for the optimisation of highbush blueberries (Vaccinium corymbosum L.) cold chain , Journal of Agricultural Engineering: Vol. 47 No. 2 (2016)
- Celeste Righi Ricco, Alberto Finzi, Viviana Guido, Elisabetta Riva, Omar Ferrari, Giorgio Provolo , Evaluation of ammonia emissions from filtration of digestate used for fertigation , Journal of Agricultural Engineering: Vol. 52 No. 3 (2021)
- Enrica Santolini, Marco Bovo, Alberto Barbaresi, Daniele Torreggiani, Patrizia Tassinari, Evaluation of microclimate in dairy farms using different model typologies in computational fluid dynamics analyses , Journal of Agricultural Engineering: Vol. 55 No. 3 (2024)
- Natalia Fumagalli, Claudia Colombo, Paolo Stefano Ferrario, Giulio Senes, Alessandro Toccolini, Suburban waterfront with ecological and recreational function: planning based on network analysis , Journal of Agricultural Engineering: Vol. 44 No. 4 (2013)
- Zhiqiang Song, Chuanxing Du, Yongcheng Chen, Dianlei Han, Xinzhong Wang, Development and test of a spring-finger roller-type hot pepper picking header , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Ernest Ekow Abano, Livingston Kobina Sam-Amoah, Ato Bart-Plange, Variation in ultrasonic frequency and time as pre-treatments to air-drying of carrot , Journal of Agricultural Engineering: Vol. 43 No. 4 (2012)
- Raffaele Cavalli, Stefano Grigolato, Andrea Sgarbossa, Productivity and quality performance of an innovative firewood processor , Journal of Agricultural Engineering: Vol. 45 No. 1 (2014)
- Xiong Bi, Hongchun Wang, Double-branch deep convolutional neural network-based rice leaf diseases recognition and classification , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
<< < 6 7 8 9 10 11 12 13 14 15 > >>
You may also start an advanced similarity search for this article.
